Adaptive DWT-SVD Domain Image Watermarking Using Human Visual Model

As digital watermarking has become an important tool for copyright protection, various watermarking schemes have been proposed in literature. Among them both discrete wavelet transform (DWT) and singular value decomposition (SVD) are commonly used. In a DWT-based watermarking scheme, the host image is decomposed into four frequency bands, and DWT coefficients in each band are modified to hide watermark information. Modification in all frequencies enables watermarking schemes using DWT robust to a wide range of attacks. However, as most transform methods, DWT decomposes images in terms of a standard basis set which is not necessarily optimal for a given image. By contrast with DWT, SVD offers a tailor-made basis for a given image which packs maximum signal energy into as few coefficients as possible. SVD is used in image processing also for its properties of stability, proportion invariance and rotation invariance. In this paper we propose a hybrid DWT-SVD domain watermarking scheme considering human visual properties. After decomposing the host image into four subbands, we apply SVD to each subband and embed singular values of the watermark into them. The embedding strength is determined by a human visual model proposed in A.S. Lewis and G. Knowles, (1992) and improved in M. Bertran et al., (2001). Our scheme has advantages of robustness for its embedding data into all frequencies and large capacity for using SVD. In addition, the use of human visual model guarantees the imperceptibility of the watermark.